Abstract: The increasing demand for electricity in the transportation sector presents challenges for power distribution networks, particularly with the widespread adoption of electric vehicles. To address these challenges, this study develops a bi-level optimization framework for determining the optimal charging and discharging schedule of plug-in hybrid electric vehicles integrated with renewable energy sources. At the upper level, the objective is to minimize feeder losses from the distribution grid operator’s perspective, while the lower level minimizes charging costs for electric vehicle owners under Time-of-Use tariffs. The framework is implemented in General Algebraic Modeling System using the Extended Mathematical Programming solver, which transforms the bi-level model into a single-level Mathematical Program with Equilibrium Constraints. A 28-bus distribution system with wind and solar resources is used as a case study, considering both summer and winter seasonal conditions. Results demonstrate that incorporating Vehicle-to-Grid capability significantly reduces system losses (up to 25%) and charging costs (up to 20%) compared to uncoordinated charging. Seasonal variations highlight the importance of renewable integration, with higher wind penetration in winter leading to greater efficiency gains. The proposed framework provides a practical and effective solution for integrating electric vehicles with renewable energy in smart distribution networks, supporting both grid stability and cost reduction.